code: def run_all_loss_fns_wrapped(self, embeddings, ref_emb, symmetric):
      loss_fns_list = self.load_valid_loss_fns()
  
      loss_fns = dict()
      for loss_fn in loss_fns_list:
          loss_name = type(loss_fn).__name__
          loss_fn = losses.SelfSupervisedLoss(
              loss_fn, symmetric=symmetric
          )
          loss_value = loss_fn(embeddings=embeddings, ref_emb=ref_emb)
          loss_fns[loss_name] = loss_value
  
      return loss_fns
  
file_path: pytorch-metric-learning/tests/losses/test_self_supervised_loss.py
imports: import unittest
  import torch
  import pytorch_metric_learning.losses
  from ..None import TEST_DEVICE, TEST_DTYPES
label_desc: Use image node_id 3 for calling the TestSelfSupervisedLoss obj's underlying member method code with example usage: obj.run_all_loss_fns_wrapped(embeddings, ref_emb, symmetric) and returns: loss_fns